Yasmeen Ahmad, managing director of strategy and outbound product management for data, analytics and AI at Google Cloud, shares his thoughts on how to unlock the potential of generative AI during the VB Transform conference.
The role of data in improving large language models (LLMs): While increasing the size of LLMs can lead to better performance, it’s not the only factor; domain-specific data plays a crucial role in enhancing the models’ capabilities:
The importance of multimodal capabilities in LLMs: Tapping into multimodal data, such as videos, images, and text documents, is critical for enterprises to fully leverage the power of LLMs:
The evolution of conversational AI: LLMs must be given semantic context and metadata to provide specific and accurate answers, and they need to be able to engage in coherent, back-and-forth conversations:
Broader implications: The advancements in generative AI are pushing the boundaries of what machines can create and what humans can imagine, blurring the lines between technology and magic. As LLMs continue to evolve and improve, they are spawning new breeds of business and redefining what is possible in the realm of AI. However, enterprises must adapt their data foundations and embrace new techniques to fully harness the potential of these powerful models.